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Questions tagged [causality]

Causal inference is a branch of scientific inquiry that seeks to understand the relationship between cause and effect. It involves studying the factors that lead to a particular outcome or event and identifying the causal relationships between them. Causal research is often used in fields such as medicine, psychology, and social sciences to identify the causes of various phenomena and to develop interventions that can effectively address them.

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Why likelihood decreasing for GOLEM algorithm

I was applying the GOLEM algorithm for casual inference using python but for some reason over iterations, my likelihood score is decreasing. Why does this happen? I have a pretty large dataset with 310127104 rows. I can't perform that because this…
Egorsky
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Estimate significance of double difference in means

this may be a trivial question. In my data, I have two groups grp1 and grp2. In each group, I have some observations assigned to the treatment group and some observations assigned to the control group. My question is whether there is a statistically…
Alex
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AR(1) Time Series Model and Reverse Causality

I came across a research where the authors hypothesized that x will cause y. The team used self-assessment survey questions to collect all the data on x and y. At time point 1, they asked respondents questions to measure both x and y (x1 and y1).…
yzhao
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Determine if one time series forecast another (in terms of trend only)

I have 2 time series, X_t and Y_t, which are on different scales. Y_t can be 0 to infinite, while X_t is limited to 0 to 100. How can I determine if the trend of X_t forecast the trend of Y_t? In other words if there is a peak in Xt, then the peak…
Ting Wai Au
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Presenting effect modification in causal graphs

I am quite new to causal inference and want to try some methods for treatment effect estimation. For this purpose, I created a the following data generation process in Python: import numpy as np n = 10000 X3 = np.random.randint(1,4, n) X2 =…
terra_cau
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Granger Causality Coefficients

Is it possible to see/extract the coefficients that the granger causality test of statsmodels assumes? In the output a linear regression is called: "". Can we find out…
pvalue
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causal_forest function in R takes forever

I am trying to run causal_forest in R but it is taking forever and it shouldn't be (because my friends are using the same file and are not encountering this issue). I am using RStudio as well. Does anyone know how to solve this problem? Note that…
pizzajona
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Visualizing pcAlgo object in ggdag?

There's documentation here (https://www.rdocumentation.org/packages/pcalg/versions/2.7-3/topics/pc) on how to run the pc algorithm for binary data. library(pcalg) ################################################## ## Using discrete…
Eisen
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How do I represent domain knowledge information with bnlearn

I am learning about Dynamic Bayesian Network models using the R package bnlearn. To this end, I am following this paper where they impose certain constraints in the form of 6 layers (Table 1 in the paper): 1 Gender, age at ALS onset 2 Onset…
Economist_Ayahuasca
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causal mediation packages with multiple mediators

I am new to R, so I apologise for any obvious errors in my post below. I'm looking to undertake some causal mediation analyses and have been looking at the package mediation. In my data I have more than one mediator I wish to fit simultaneously, and…
Ron
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How can I run pycausalimpact to determine and measure causation?

I came across pycausalimpact recently. https://pypi.org/project/pycausalimpact/ import numpy as np import pandas as pd from statsmodels.tsa.arima_process import ArmaProcess from causalimpact import CausalImpact np.random.seed(12345) ar = np.r_[1,…
ASH
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Problem with the `pdag2allDags` and `addBgKnowledge` functions on pcalg package

I am starting to use the pcalg package, and I am having some doubts regarding the functions pdag2allDags and addBgKnowledge: I am using the sample data gmG provided by the package library(pcalg) library(Rgraphviz) data("gmG") df<-gmG$x suffStat <-…
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is conditioning only on propensity score sufficient to CATE estimation?

I have read the paper " Adapting Neural Networks for the Estimation of Treatment Effects", which suggests a neural network architecture called Dragonnet for the estimation of treatment…
devcloud
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Causal Inference for new samples

I am new to the causal inference field and I am trying to figure some things up. I am following this snippet of code from dowhy library documentation ( https://microsoft.github.io/dowhy/example_notebooks/dowhy_ihdp_data_example.html ). My question…
robertg
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Sorting list of vector clocks (total order)?

I understand that vector clocks only provide a partial order. So you can't directly sort them. For this reason you use a tie-breaker for vectors that are concurrent, resulting in a total order. However sorting the vector clocks so that every cause…
Benjoyo
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